janice blogs

  If your Salesforce org has been around for more than a year, chances are you’ve seen duplicates pop up. The same company shows up twice with slightly different names. A sales rep isn’t sure which account to use. Marketing swears they already contacted that lead. None of this is unusual—and it’s not because your team is careless. In fact, studies show that around 30% of CRM data becomes inaccurate every year , mostly due to everyday human behavior. People abbreviate company names, make small typos, or enter data differently depending on where it’s coming from. Salesforce, by default, struggles with this. That’s where fuzzy matching comes in. Fuzzy matching exists to deal with reality. Data isn’t perfect, and Salesforce shouldn’t expect it to be. Salesforce’s standard matching logic relies on exact matches. If two records don’t match character for character, Salesforce treats them as completely different. That works fine for things like email addresses or record IDs. But for names...

  If you work inside a large U.S. enterprise—especially in sales, marketing, RevOps, or anything related to CRM—you’ve probably felt the frustration of watching a great lead slip through the cracks. Maybe it sat in a queue too long. Maybe it went to the wrong rep. Maybe no one could tell whether it belonged to an existing account or a brand-new logo. And maybe, by the time someone figured it out, the prospect had already moved on to a competitor. These moments don’t usually happen because a team lacks talent or drive. They happen because the infrastructure behind the scenes isn’t catching up to the pace at which modern leads enter the business. The truth is, enterprise sales today isn’t just about finding leads—it’s about knowing exactly who they belong to, where they should go, and how to get them there fast. That’s why lead-to-account matching and intelligent routing are now front and center in many conversations around revenue efficiency and scale. In theory, matching a lead...